Most Canadian organizations are moving from experimenting with AI to adopting it at scale. They are leveraging assistants, automating tasks and deploying agents capable of reasoning, planning and acting. But a significant gap still exists between testing AI use cases and transforming business operations with enterprise-wide implementation.
According to research from IDC in partnership with Lenovo, 88% of AI pilots fail to reach production. Our view: AI is only as good as the data it pulls from. To understand why most pilots have not been effective, we must look at the foundation of any AI project—data that is trusted and in context.
AI Needs Trusted Data, in Context
Enterprise AI depends on trusted, secured, governed and contextualized data. AI agents are no longer just generating content. They are making decisions, executing tasks and interacting with business processes.
Agents need access not only to data, but also to an organization's policies, processes, client information, operational records and business rules. Without that context, they can generate what look like convincing outputs while making decisions that are inaccurate, inconsistent or non-compliant. Getting the data foundation right has never been more important.
Partnering to Deliver Agentic AI at Scale
Successful enterprise AI is enabled by interconnected layers forming a trusted AI stack:
- The trusted data foundation in context
- The business systems that run the enterprise
- The large language models that reason over that data
- The orchestration platforms that embed agentic AI into core workflows
A major airline offers an example of this approach in practice. To support aircraft maintenance and regulatory compliance, the airline leverages an ecosystem of technology partners spanning content management, enterprise applications and cloud infrastructure. Maintenance records, engineering documents and business process data are connected across systems, giving AI agents the trusted context needed to support technicians and operational teams.
This connected ecosystem enables AI systems to surface critical information, recommend next steps and support faster decision-making while maintaining the safety, traceability and compliance requirements essential to airline operations. The value comes not from the model alone, but from combining business processes with a secure, contextualized data foundation and AI reasoning and workflow orchestration.
Trust Is the Real Competitive Advantage
Agentic AI has the potential to transform how organizations operate, but success will depend on more than the performance of individual models or agents. For Canadian businesses, the next wave of AI won't be won by whoever deploys the most agents. It will be won by whoever builds the most trusted stack, turning AI's promise into real business advantage.
About OpenText
Founded in Waterloo, Ontario in 1991, OpenText is a world leader in data management for enterprise AI, Canadian in roots and global in reach. The company provides the secure data foundation in the AI stack, the trusted context that makes credible AI outcomes possible.
The company gives clients the choice to transform and operate at their best: deployment on premises or in the cloud, with the type of cloud they need, public, private or sovereign, and to integrate with any enterprise-grade AI language model.
Powered by trust and dedication, OpenText colleagues proudly serve more than 120,000 enterprise clients in 80 countries worldwide.
